Welcome to Ziheng Yang Lab

Our group is based at Department of Genetics, Evolution and Environment (GEE), University College London (UCL). We are connected to the UCL Centre for Computational Biology and the Centre for Life’s Origins and Evolution (CLOE) in UCL. We have ongoing collaborations with scientists around the world, including UCL statistics (Professor Petros Dellaportas), California, Duke, Seattle, China, Japan, Zurich, and Heidelberg.

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We are a small group of friendly and highly motivated researchers with varied backgrounds, including evolutionary genetics, genomics, computer science and statistics. We develop statistical models and computer software for population genetic and phylogenetic analysis of DNA or protein sequence data, both from different species and from the same species. We make heavy use of maximum likelihood and Bayesian methods, and develop sophisticated Markov chain Monte Carlo algorithms that can meet the challenges of huge datasets resulting from genome projects. Analysis of genome-scale datasets is also a major undertaking in the group, which helps to test the new methods we develop and motivate the methodological work.

Current projects in the group include (i) development and implementation of the multispecies coalescent model to incorporate cross-species gene flow, using both maximum likelihood and Bayesian MCMC, (ii) Bayesian estimation of species divergences integrating information from both the fossil record and molecular sequence data, (iii) mixing efficiency of MCMC, especially trans-model MCMC, and (iv) analysis of genome-scale datasets from viruses, mammals, and plants.

We welcome bright students with background in probability theory (e.g., Markov chains and stochastic processes), mathematical statistics (in particular computation-intensive methods such as MCMC), computer science (such as high-performance computing, C programming), as well as population genomics and phylogenomics to join us as MSc/PhD students. If you are good at one of those areas (probability and statistics, computer science, and evolution and genomics) and hope to improve your skills in the other areas, then there is a high chance that we have the right projects for you.